Video transcoding

Render every delivery version of a finished video from one master and play-test each one, so a broken file is found before the client opens the link.

Media / AUTOMATE.md

When the video render finishes, check that every expected rendition exists and plays, then post the list of versions and flag any that fail to load.

Ready-made: Rendition Completeness Check

The job, and what good looks like.

Encoding is treated as the last five minutes of a job, so it is the step that goes wrong. A queue is submitted, the render finishes, and nobody opens the files. The broken one is a single rendition at one bitrate that the client's phone will not play, discovered on the morning of a launch. This workflow keeps one master per finished video, runs it through the agreed set of sizes, and checks every output for duration, size, and a real playback sample before anything is sent. Anything that fails goes on a short list with the file name, and the delivery is held until it is re-run or consciously dropped. Delivery recipes are recorded per client, so the next job for the same account is not specified from memory. The editor still decides which master is final and which versions the client should have; the workflow only makes sure what was promised actually plays.

When it is handled

  • Every expected rendition present after a render
  • Each version played before release
  • Bad encodes caught before the link ships
  • One master, one delivery recipe

Works with tools like

  • AWS MediaConvert
  • Mux
  • Cloudflare Stream
  • Cloudinary
  • Bunny.net

Ready-made automations. Pick the one that fits.

Each one is a plain-language document. Run it as it is, or change the timing, the rules and the tools to match your team.

You stay in charge.
At every step.

It checks and files. Every creative call stays yours.

  • It never deletes on its own

    It checks, lists and files. Deleting or formatting anything waits for your OK.

  • Undo a move you don't want

    Every step is recorded, and files it moved or renamed can be put back.

  • Your drives stay yours

    It works on the folders you point it at, on your computer. Nothing is uploaded to a new library.

Rendition Completeness Check

Approve before it posts in Slack?

ReviewApprove

Before you download.

Where does it run?
On your Mac or Windows computer, in the background. It keeps working after you close its window, and only reaches the folders and apps you connect for each automation.
How does it connect to our CRM and other tools?
Through each app's own connection where it offers one, signed in once by you, or by using the app in a browser the way you would. Each automation gets only the connections you give it, and the tools a page names are examples you can swap for your own.
Does it run when my computer is asleep?
It keeps your computer awake while a job runs and just before a scheduled one. While the computer is closed or off, nothing runs; when it wakes, it checks the inbox, calendar and other sources it watches for anything that arrived meanwhile.
How does my team use it?
Each person who runs automations installs the app. Keep a project in a shared folder, such as Google Drive or a network drive, and teammates can open it and follow every run, while one person owns it and runs it.
Do I need anyone technical to set it up?
No. Download the app, add an automation in plain words, and connect only what that job needs. Nothing runs until you switch it on.

Already have tools for this? Here is the difference.

Presets and actions in your editor

Repeating the same edit across many files.

They can't check a delivery against an approval or tell you a card didn't copy.

Flowchart automation tools

Moving data between cloud apps.

They rarely reach local drives, and every exception becomes another branch.

Doing it by hand

Knowing exactly what happened.

It is the part of the job that waits until midnight.

AUTOMATE.md

Your routine, written in plain words. It runs on its own, follows your rules, handles the exceptions a flowchart can't, and asks you when it matters. The file stays yours, whichever AI model runs it.

Start with one job.
Make it your own.

macOS — coming soon
  1. 1

    Get the app

    It runs on your computer, next to your files.

  2. 2

    Add the automation

    Paste the instructions into the app, or save them as a file next to your work.

  3. 3

    Try it, then turn it on

    Run it once and check the result. It only runs on its own once you switch it on.